Triple

T6490969
Position Surface form Disambiguated ID Type / Status
Subject River Esk E148034 entity
Predicate flowsThrough P225 FINISHED
Object Danby E106908 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Danby | Statement: [River Esk, flowsThrough, Danby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danby
Context triple: [River Esk, flowsThrough, Danby]
  • A. Danby
    Danby is a small rural town in Tompkins County, New York, known for its scenic landscapes and proximity to the city of Ithaca.
  • B. Danby chosen
    Danby is a small rural village in North Yorkshire, England, known for its scenic setting within the North York Moors National Park.
  • C. Blodgett
    Blodgett is a surname of English origin borne by various notable individuals across fields such as politics, business, and the arts.
  • D. Kenmore
    Kenmore is a long-standing American brand of home appliances, particularly known for its refrigerators, washers, dryers, and kitchen equipment sold through major retailers.
  • E. Kenmore
    Kenmore is a major Boston transit station and surrounding neighborhood hub that serves as a key access point to Fenway Park, Boston University, and the Kenmore Square area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a9a8d8481908d88e5c9f0c773f7 completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c653bcb63081908be29abd0084d266 completed March 27, 2026, 9:54 a.m.
Created at: March 22, 2026, 4:53 p.m.